Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
29,558 documents
This note presents a stock screen combining three conditions: price amplitude above 1%, a prior session 9:15 matched auction price at the limit-down level, and the 20-day moving average above the 120-day average. It suggests selecting the top n qualifying…
This note describes an equity screen that selects stocks with daily turnover between 3% and 12%, three consecutive declining sessions, and company size above 200 million. It provides example rule implementations and ranks qualifying stocks by size in the…
This A-share screening proposal combines an amplitude threshold above 1, a requirement that the outstanding convertible-bond name field is nonempty, and a same-day candlestick reversal condition described as a morning star. The document says to rank…
This Expert Advisor concept opens buy and sell positions together, then adds trades at fixed pip intervals when price moves against an initial position. Added position sizes may grow by a configured multiplier, while the system seeks to close trades or the…
This proposed A-share screen combines a price-range condition, a recent large daily gain, and a dividend payout criterion. The initial logic looks for an intraday range exceeding a volatility-based threshold, at least one daily gain of 10% or more within the…
This article describes a high-frequency trading tactic that tries to profit from a large buyer who repeatedly raises a displayed bid. The trader first moves the market up by a tick, watches whether the buyer follows, and continues stepping prices higher if…
This note describes a Chinese equity screen for stocks with RSI below 65, negotiable market value between 5 billion and 10 billion yuan, and a nonempty field indicating an outstanding convertible bond. The Python example calculates a 14-period RSI, applies…
This document explains copula-based measures for comparing financial return series by separating marginal distributions from dependence. It presents Spearman’s rho as a rank-based dependence measure and contrasts it with Pearson correlation, which captures…
The note proposes adding a 20-period average true range (ATR) volatility factor to a trading strategy, with the aim of improving its Sharpe ratio. It describes a regime-dependent relationship: higher ATR is associated with stronger returns in bull markets,…
The document describes a dynamic balance point indicator calculated for a selected period and displayed in the context of the current chart timeframe. It claims the calculation avoids the recalculation problems often associated with multi-timeframe…
The article presents a Chinese equity screening rule for robot-themed companies. It selects stocks with turnover between 3% and 12%, first-level bid volume greater than first-level ask volume, and circulating market capitalization below 10 billion yuan. The…
This example describes a short-term price timing strategy for a gold futures contract. It calculates an AR indicator from recent daily bars by comparing the accumulated distance from open to high with the distance from open to low, scaled as a percentage.…
The document explains six Bitcoin indicators used to interpret investor sentiment and supply behavior: realized price, net unrealized profit/loss (NUPL), coins held or presumed lost, monthly long-term-holder position change, liquid versus illiquid supply,…
This proposed screen looks for non-ST Chinese stocks before 10 a.m. with amplitude greater than one, a pattern described as a five-step limit-up method, and an opening price near the ten-day moving average. The accompanying example translates parts of that…
This Chinese stock screen combines three filters: at least five moving averages overlap, the prior day’s exchange leaderboard shows participation by large institutions or funds, and the company’s 2019 payout ratio exceeds 25%. The article interprets the…
These release notes describe changes across versions of the VeighNa trading framework. For quantitative research, notable updates include a cross-sectional percentile ranking function, revised factor and signal performance analysis, an added VWAP matching…
This Chinese stock-screening strategy selects shares with turnover between 3% and 12%, a positive product of price change and large-order net buying, and at least one limit-up event in the recent month. The article presents these filters as a combination of…
This stock-selection approach ranks shares by capital inflow, including measures such as northbound investment or margin financing, and combines that ranking with a moving-average trend filter. The stated conditions include a 20-day average above the 120-day…
This Chinese stock-screening note combines three conditions: amplitude above 1, a shortening negative MACD histogram on a 15-minute chart, and three consecutive declining sessions. It frames amplitude as a volatility filter and the histogram change as a…
The document outlines a Chinese-equity screen for robot-concept stocks that combines a minimum daily trading-range condition with limits on total and freely tradable market capitalization. It also calls for profitable companies, described in the refined…
This summary compares two research reports on protecting portfolios during market stress: one published before a major volatility episode and another written afterward. It frames their comparison around how investors assess defensive strategies before a…
This document describes a Chinese stock screen using price amplitude, a recent three-session sequence of rising closes described as three consecutive limit-up moves, and a prior-day actual turnover range. The rationale is that large price movement and…
This document outlines a technical stock screen combining a price-amplitude threshold, a morning star candlestick pattern, and a negative MACD reading from two days earlier. It describes the pattern and recent MACD condition as a way to look for stocks that…
This notebook demonstrates a workflow for running an online portfolio moving average reversion algorithm in Zipline and analyzing its output with pyfolio. The example applies OLMAR to a fixed basket of seven stocks, estimates relative mean deviations from a…